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All Journal International Journal of Applied Power Engineering (IJAPE) Bulletin of Electrical Engineering and Informatics
Kambhampati Venkata Govardhan Rao
St. Martin’s Engineering College
Electrical & Electronics Engineering

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Super-twisting sliding mode control for enhanced performance of grid-connected PV systems with H-bridge multilevel inverter CH. Venkata Amarnadh; T. Vijay Muni; T. Anuradha Devi; Rakesh Teerdala; M. Kiran Kumar; Kambhampati Venkata Govardhan Rao
International Journal of Applied Power Engineering (IJAPE) Vol 15, No 2: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v15.i2.pp464-479

Abstract

This paper presents an enhanced control strategy for a grid-connected photovoltaic (PV) system employing a novel H-bridge multilevel inverter (MLI). The key contribution of this work lies in replacing the conventional proportional-integral (PI) controller with a super-twisting sliding mode controller (STSMC) for DC-link voltage regulation. Unlike earlier approaches that suffer from slow response, steady-state errors, and limited robustness under varying solar and temperature conditions, the proposed STSMC ensures faster transient response, finite-time convergence, and strong disturbance rejection without the chattering problem of classical sliding mode controllers. Another distinctive aspect of this study is the integration of STSMC with direct model predictive control (DMPC) for grid current regulation, enabling accurate reference current generation and improved synchronization. The novel H-bridge MLI topology further enhances system efficiency by reducing the number of switches while producing a seven-level output with lower total harmonic distortion (THD). Simulation results demonstrate that the proposed strategy achieves superior performance compared to the conventional PI-based system, with improvements in voltage stability, current quality, and reduced THD. These findings confirm the novelty and effectiveness of the proposed control scheme for reliable and efficient PV grid integration.
Empowering energy management: anomaly detection in smart meter data for proactive consumption control Batchalakuri Jyothi; Bhavana Pabbuleti; Beeravalli Mounika; Hrushitha Kalapala; Meda Uma Santhosh Chandra; Sanaboina Sai Srilakshmi; Bommasani Ganesh Babu; Kambhampati Venkata Govardhan Rao; Malligunta Kiran Kumar; Rami Reddy Chilakala
Bulletin of Electrical Engineering and Informatics Vol 15, No 3: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v15i3.10957

Abstract

The increasing deployment of smart energy meters (SEMs) has enabled real-time monitoring of energy consumption, but the vast data generated makes it challenging to detect anomalies that may indicate inefficiencies, faults, or unauthorized usage. This study aims to enhance energy management by developing a hybrid anomaly detection framework that improves accuracy while providing actionable insights for consumers. The proposed method integrates statistical and machine learning (ML) approaches, specifically Z-score, local outlier factor (LOF), one-class support vector machine (SVM), and isolation forest (iForest), to analyze simulated smart meter data. An anomaly is flagged only when identified by all four methods, thereby reducing false positives and improving reliability. The framework is implemented in an interactive dashboard built with streamlit, offering real-time visualization, peak-time alerts, usage forecasts, and personalized consumption suggestions. Results demonstrate that the hybrid approach outperforms single-method models, achieving higher detection accuracy and practical applicability. The findings highlight the potential of combining complementary detection techniques with proactive feedback to empower consumers, reduce energy wastage, and support sustainable energy management. This work provides a scalable foundation for future real-time deployment in smart grids and microgrid environments.
Co-Authors Batchalakuri Jyothi Beeravalli Mounika Bhavana Pabbuleti Bommasani Ganesh Babu CH. Venkata Amarnadh Hrushitha Kalapala M. Kiran Kumar Malligunta Kiran Kumar Meda Uma Santhosh Chandra Rakesh Teerdala Rami Reddy Chilakala Sanaboina Sai Srilakshmi T. Anuradha Devi T. Vijay Muni